shunsunsun / term-enrichment-analysis

Term Enrichment Analysis

Repository containing R code for ontology, pathway and kinase substrate enrichment analysis (with examples) used in this study:

Drug ranking using machine learning (DRUML) systematically predicts the efficacy of anti-cancer drugs

Henry Gerdes 1, Pedro Casado 1, Arran Dokal 1, Maruan Hijazi 1, #, Nosheen Akhtar1, 3, Ruth Osuntola 4, Vinothini Rajeeve 4, Jude Fitzgibbon 5, Jon Travers 6, David Britton 1,2, Shirin Khorsandi 7 & Pedro R. Cutillas 1,4,8*

1 Cell Signalling & Proteomics Group, Centre for Genomics & Computational Biology, Barts Cancer Institute, Queen Mary University of London, Charterhouse Square, London, EC1M 6BQ, United Kingdom 2 Current address: Kinomica Ltd, Alderley Park, Alderley Edge, Macclesfield SK10 4TG, United Kingdom 3 Department of Biological Sciences, National University of Medical Sciences, Rawalpindi, Pakistan 4 Mass spectrometry Laboratory, Barts Cancer Institute, Queen Mary University of London, Charterhouse Square, London, EC1M 6BQ, United Kingdom 5 Personalised Medicine Group, Centre for Genomics & Computational Biology, Barts Cancer Institute, Queen Mary University of London, Charterhouse Square, London, EC1M 6BQ, United Kingdom 6 Astra Zeneca Ltd, 1 Francis Crick Avenue, Cambridge Biomedical Campus, Cambridge, CB2 0AA, United Kingdom 7 Kings College London, Denmark Hill, Brixton, London SE5 9RS, United Kingdom 8 The Alan Turing Institute, The British Library, 2QR, 96 Euston Rd, London NW1 2DB, United Kingdom

Copyright

The copyright holder for these data is the author. This resource is made available under a Creative Commons Attribution-NonCommercial-NoDerivatives CC-BY-NC-ND 4.0 International license.